Oral Microbiome - Most abundant across site 2021-03-25
Florentin CONSTANCIAS
2021-03-25
- Fin most abundant taxa across sites:
- Data loading:
- Fig1 Identification of predominant streptococcus species at all sites
- Identification of predominant streptococcus species at all sites
- Fig2 Overall bacterial activity of selected species
- S1A – pathway expression of selected streptococcus species in saliva vs. tongue in health
- FigS1B: pathway expression of selected streptococcus species in saliva vs. plaque in health
Fin most abundant taxa across sites:
sapply(c(biobakery_function, alpha, beta, taxa, norm, heat, varia), source, chdir = TRUE)Data loading:
input <- list(metpahlan_ps = "~/Documents/GitHub/oral-microbiome/data/processed/metaphlan_ps.RDS",
motus_ps = "~/Documents/GitHub/oral-microbiome/data/processed/motus/physeq.RDS",
pathway_ps = "~/Documents/GitHub/oral-microbiome/data/processed/humann_pw_ps.RDS",
kegg_ps = "~/Documents/GitHub/oral-microbiome/data/processed/humann_kegg_ps.RDS",
l4c_ps = "~/Documents/GitHub/oral-microbiome/data/processed/humann_l4c_ps.RDS",
go_ps = "~/Documents/GitHub/oral-microbiome/data/processed/humann_go_ps.RDS",
infogo_ps = "~/Documents/GitHub/oral-microbiome/data/processed/humann_infogo_ps.RDS",
metac_ps = "~/Documents/GitHub/oral-microbiome/data/processed/humann_metac_ps.RDS",
pfam_ps = "~/Documents/GitHub/oral-microbiome/data/processed/humann_pfam_ps.RDS")purrr::map(input,
readRDS) -> objectssample_data(objects$metpahlan_ps$physeq)$Site_Health <- paste0(sample_data(objects$metpahlan_ps$physeq)$Oral_Site,
"_",
sample_data(objects$metpahlan_ps$physeq)$Health_status)Fig1 Identification of predominant streptococcus species at all sites
This figure is good, but with the approach we decided focusing solely on streptococcus species We should change it a bit so that it shows top 10 streptococcus species across all three sites
objects$metpahlan_ps$physeq -> tmp
# subset_samples(Health_status == "Healthy control") %>%
# subset_samples(Oral_Site %in% c("SALIVA", "TONGUE_BIOFILM")) -> tmp
tmp %>%
subset_taxa(Genus %in% c("Streptococcus")) %>%
physeq_most_abundant(physeq = .,
group_var = "Oral_Site",
ntax = 10,
tax_level = "Species") -> ma_saliva_tongue_streptmp %>%
transform_sample_counts(function(x) x/sum(x) * 100) %>%
phyloseq::subset_taxa(Species %in% ma_saliva_tongue_strep) %>%
phyloseq_ampvis_heatmap(transform = FALSE,
group_by = "Subject",#treatment
facet_by = c("Oral_Site", "Health_status", "Subject"),
ntax = 100,
tax_aggregate = "Species",
tax_add = NULL) -> p## Warning: There are only 16 taxa, showing allp + facet_grid(. ~ Oral_Site + Health_status, scales = "free", space = "free") +
scale_fill_viridis_c(breaks = c(0, 0.01, 1, 10, 25, 50, 75, 100),
labels = c(0, 0.01, 1, 10, 25,50, 75, 100),
trans = scales::pseudo_log_trans(sigma = 0.1)) +
theme_classic() +
theme(axis.text.x = element_text(angle = 90, hjust = 1, size = 6)) +
theme(axis.text.y = element_text(angle = 0, size = 8))
Identification of predominant streptococcus species at all sites
Fig1A: predominant streptococcus species across all samples in health
objects$metpahlan_ps$physeq %>%
subset_samples(Health_status == "Healthy control") -> tmp
# subset_samples(Oral_Site %in% c("SALIVA", "TONGUE_BIOFILM")) -> tmp
tmp %>%
subset_taxa(Genus %in% c("Streptococcus")) %>%
physeq_most_abundant(physeq = .,
group_var = "Oral_Site",
ntax = 10,
tax_level = "Species") -> ma_saliva_tongue_streptmp %>%
transform_sample_counts(function(x) x/sum(x) * 100) %>%
phyloseq::subset_taxa(Species %in% ma_saliva_tongue_strep) %>%
phyloseq_ampvis_heatmap(transform = FALSE,
group_by = "Subject",#treatment
facet_by = c("Oral_Site", "Health_status", "Subject"),
ntax = 100,
tax_aggregate = "Species",
tax_add = NULL) -> p## Warning: There are only 16 taxa, showing allp + facet_grid(. ~ Oral_Site + Health_status, scales = "free", space = "free") +
scale_fill_viridis_c(breaks = c(0, 0.01, 1, 10, 25, 50, 75, 100),
labels = c(0, 0.01, 1, 10, 25,50, 75, 100),
trans = scales::pseudo_log_trans(sigma = 0.1)) +
theme_classic() +
theme(axis.text.x = element_text(angle = 90, hjust = 1, size = 6)) +
theme(axis.text.y = element_text(angle = 0, size = 8))
### Fig1B: predominant streptococcus species saliva vs. tongue samples in health
objects$metpahlan_ps$physeq %>%
subset_samples(Health_status == "Healthy control") %>%
subset_samples(Oral_Site %in% c("SALIVA", "TONGUE_BIOFILM")) -> tmp
tmp %>%
subset_taxa(Genus %in% c("Streptococcus")) %>%
physeq_most_abundant(physeq = .,
group_var = "Oral_Site",
ntax = 10,
tax_level = "Species") -> ma_saliva_tongue_streptmp %>%
transform_sample_counts(function(x) x/sum(x) * 100) %>%
phyloseq::subset_taxa(Species %in% ma_saliva_tongue_strep) %>%
phyloseq_ampvis_heatmap(transform = FALSE,
group_by = "Subject",#treatment
facet_by = c("Oral_Site", "Health_status", "Subject"),
ntax = 100,
tax_aggregate = "Species",
tax_add = NULL) -> p## Warning: There are only 13 taxa, showing allp + facet_grid(. ~ Oral_Site + Health_status, scales = "free", space = "free") +
scale_fill_viridis_c(breaks = c(0, 0.01, 1, 10, 25, 50, 75, 100),
labels = c(0, 0.01, 1, 10, 25,50, 75, 100),
trans = scales::pseudo_log_trans(sigma = 0.1)) +
theme_classic() +
theme(axis.text.x = element_text(angle = 90, hjust = 1, size = 6)) +
theme(axis.text.y = element_text(angle = 0, size = 8))
ma_saliva_tongue_strep## [1] "Streptococcus_australis" "Streptococcus_cristatus"
## [3] "Streptococcus_gordonii" "Streptococcus_infantis"
## [5] "Streptococcus_mitis" "Streptococcus_mutans"
## [7] "Streptococcus_oralis" "Streptococcus_parasanguinis"
## [9] "Streptococcus_salivarius" "Streptococcus_sanguinis"
## [11] "Streptococcus_sp_A12" "Streptococcus_sp_F0442"
## [13] "Streptococcus_sp_HMSC071D03"ma_saliva_tongue_strep_sel <- c("Streptococcus_parasanguinis",
"Streptococcus_salivarius",
"Streptococcus_infantis")Fig1C: predominant streptococcus species saliva vs. plaque in health
objects$metpahlan_ps$physeq %>%
subset_samples(Health_status == "Healthy control") %>%
subset_samples(Oral_Site %in% c("SALIVA", "SUBGINGIVAL_PLAQUE")) -> tmp
tmp %>%
subset_taxa(Genus %in% c("Streptococcus")) %>%
physeq_most_abundant(physeq = .,
group_var = "Oral_Site",
ntax = 10,
tax_level = "Species") -> ma_saliva_plaque_streptmp %>%
transform_sample_counts(function(x) x/sum(x) * 100) %>%
phyloseq::subset_taxa(Species %in% ma_saliva_plaque_strep) %>%
phyloseq_ampvis_heatmap(transform = FALSE,
group_by = "Subject",#treatment
facet_by = c("Oral_Site", "Health_status", "Subject"),
ntax = 100,
tax_aggregate = "Species",
tax_add = NULL) -> p## Warning: There are only 13 taxa, showing allp + facet_grid(. ~ Oral_Site + Health_status, scales = "free", space = "free") +
scale_fill_viridis_c(breaks = c(0, 0.01, 1, 10, 25, 50, 75, 100),
labels = c(0, 0.01, 1, 10, 25,50, 75, 100),
trans = scales::pseudo_log_trans(sigma = 0.1)) +
theme_classic() +
theme(axis.text.x = element_text(angle = 90, hjust = 1, size = 6)) +
theme(axis.text.y = element_text(angle = 0, size = 8))
ma_saliva_plaque_strep## [1] "Streptococcus_anginosus_group" "Streptococcus_australis"
## [3] "Streptococcus_cristatus" "Streptococcus_gordonii"
## [5] "Streptococcus_infantis" "Streptococcus_mitis"
## [7] "Streptococcus_mutans" "Streptococcus_oralis"
## [9] "Streptococcus_parasanguinis" "Streptococcus_salivarius"
## [11] "Streptococcus_sanguinis" "Streptococcus_sobrinus"
## [13] "Streptococcus_sp_oral_taxon_056"ma_saliva_plaque_strep_sel <- c("Streptococcus_oralis",
"Streptococcus_sanguinis",
"Streptococcus_gordonii")Fig2 Overall bacterial activity of selected species
Load pathway abundance table and have a look:
objects$pathway_ps$physeq %>%
humann2_species_contribution(meta_data_var = c("Subject", "sample_Sample" ,"Type", "Oral_Site", "Health_status")) %>%
separate(Feature, into = c("code", "name"), sep = ": ", remove = FALSE) %>%
dplyr::filter(!is.na(name)) -> pwy## Warning in speedyseq::psmelt(.): The sample variables:
## Sample
## have been renamed to:
## sample_Sample
## to avoid conflicts with special phyloseq plot attribute names.## Warning: Expected 2 pieces. Missing pieces filled with `NA` in 720 rows [1029,
## 1903, 1961, 2338, 2461, 2854, 3562, 3891, 4578, 5649, 5690, 5849, 5854, 6607,
## 6843, 7028, 7077, 7309, 7819, 8576, ...].pwy %>%
distinct(name, .keep_all = TRUE) %>%
DT::datatable()Fig2A: box plot species saliva vs. tongue
ma_saliva_tongue_strep_sel## [1] "Streptococcus_parasanguinis" "Streptococcus_salivarius"
## [3] "Streptococcus_infantis"pwy %>%
dplyr::filter(Health_status == "Healthy control",
Oral_Site %in% c("SALIVA", "TONGUE_BIOFILM")) %>%
# filter(RNA_DNA > mean(RNA_DNA, na.rm = TRUE)) %>%
# dplyr::filter(grepl("ose",name)) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "Species",
y_plot = "log2(RNA_DNA)",
color = "Oral_Site",
fill = "Oral_Site",
shape = NULL,
filter_species = ma_saliva_tongue_strep_sel,
facet_formula = ". ~ .",
export_legend = TRUE) -> plot## Warning in if (filter_species != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot + ggpubr::rotate()
plot$plot$data %>%
ggpubr::compare_means(RNA_DNA ~ Oral_Site,
group.by = c("Species"),
data = .,
method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) %>%
DT::datatable()Fig2B: log DNA/Log RNA plots of species saliva vs. tongue
pwy %>%
dplyr::filter(Health_status == "Healthy control",
Oral_Site %in% c("SALIVA", "TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_plot(x_plot = "log10(DNA)",
y_plot = "log10(RNA)",
color = "Species",
fill = "Species",
shape = "Genus",
group = "Species",
filter_species = ma_saliva_tongue_strep_sel,
facet_formula = "Oral_Site ~ .") -> plot## Warning in if (filter_species != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot 
plot$plot$data %>%
select(-id, -sample_Sample, Health_status) %>%
group_by(Subject, Oral_Site) %>%
add_count(name = "count_per") %>%
slice_max(order_by = RNA, n = 3) %>%
DT::datatable()plot$plot$data %>%
select(-id, -sample_Sample, Health_status) %>%
group_by(Subject, Oral_Site) %>%
add_count(name = "count_per") %>%
slice_max(order_by = RNA_DNA, n = 3) %>%
DT::datatable()Fig2C: box plot species saliva vs. plaque
pwy %>%
dplyr::filter(Health_status == "Healthy control",
Oral_Site %in% c("SALIVA", "SUBGINGIVAL_PLAQUE")) %>%
# filter(RNA_DNA > mean(RNA_DNA, na.rm = TRUE)) %>%
# dplyr::filter(grepl("ose",name)) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "Species",
y_plot = "log2(RNA_DNA)",
color = "Oral_Site",
fill = "Oral_Site",
shape = NULL,
filter_species = ma_saliva_plaque_strep_sel,
facet_formula = ". ~ .",
export_legend = TRUE) -> plot## Warning in if (filter_species != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot + ggpubr::rotate()
plot$plot$data %>%
ggpubr::compare_means(RNA_DNA ~ Oral_Site,
group.by = c("Species"),
data = .,
method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) %>%
DT::datatable()Fig2D: log DNA/Log RNA plots of species saliva vs. plaque
pwy %>%
dplyr::filter(Health_status == "Healthy control",
Oral_Site %in% c("SALIVA", "SUBGINGIVAL_PLAQUE")) %>%
humann2_RNA_DNA_plot(x_plot = "log10(DNA)",
y_plot = "log10(RNA)",
color = "Species",
fill = "Species",
shape = "Genus",
group = "Species",
filter_species = ma_saliva_plaque_strep_sel,
facet_formula = "Oral_Site ~ .") -> plot## Warning in if (filter_species != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot 
plot$plot$data %>%
select(-id, -sample_Sample, Health_status) %>%
group_by(Subject, Oral_Site) %>%
add_count(name = "count_per") %>%
slice_max(order_by = RNA, n = 3) %>%
DT::datatable()plot$plot$data %>%
select(-id, -sample_Sample, Health_status) %>%
group_by(Subject, Oral_Site) %>%
add_count(name = "count_per") %>%
slice_max(order_by = RNA_DNA, n = 3) %>%
DT::datatable()S1A – pathway expression of selected streptococcus species in saliva vs. tongue in health
pwy %>%
dplyr::filter(Health_status == "Healthy control",
Oral_Site %in% c("SALIVA", "TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Oral_Site",
fill = "Oral_Site",
shape = NULL,
filter_species = ma_saliva_tongue_strep_sel,
facet_formula = " . ~ Health_status + Species",
export_legend = TRUE) -> plot## Warning in if (filter_species != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot
plot$plot$data %>%
# mutate(log2RNA_DNA = log2(RNA_DNA)) %>%
ggpubr::compare_means(RNA_DNA ~ Oral_Site,
group.by = c("Species","Feature"),
data = .,
# method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) -> diff_signif
diff_signif %>%
DT::datatable()FigS1B: pathway expression of selected streptococcus species in saliva vs. plaque in health
pwy %>%
dplyr::filter(Health_status == "Healthy control",
Oral_Site %in% c("SALIVA", "SUBGINGIVAL_PLAQUE")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Oral_Site",
fill = "Oral_Site",
shape = NULL,
filter_species = ma_saliva_plaque_strep_sel,
facet_formula = " . ~ Health_status + Species",
export_legend = TRUE) -> plot## Warning in if (filter_species != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot
plot$plot$data %>%
# mutate(log2RNA_DNA = log2(RNA_DNA)) %>%
ggpubr::compare_means(RNA_DNA ~ Oral_Site,
group.by = c("Species","Feature"),
data = .,
# method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) -> diff_signif
diff_signif %>%
DT::datatable()Fig 3. Pathway activity of selected species
Fig3A: significant pathway expression by candidate species saliva versus tongue in health
redo main plot + stats
pwy %>%
dplyr::filter(Health_status == "Healthy control",
Oral_Site %in% c("SALIVA", "TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Oral_Site",
fill = "Oral_Site",
shape = NULL,
filter_species = ma_saliva_tongue_strep_sel,
facet_formula = " . ~ Health_status + Species",
export_legend = TRUE) -> plot## Warning in if (filter_species != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot
plot$plot$data %>%
# mutate(log2RNA_DNA = log2(RNA_DNA)) %>%
ggpubr::compare_means(RNA_DNA ~ Oral_Site,
group.by = c("Species","Feature"),
data = .,
# method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) -> diff_signif
diff_signif %>%
DT::datatable()pwy %>%
dplyr::filter(Health_status == "Healthy control") %>%
dplyr::filter(Oral_Site %in% c("SALIVA", "TONGUE_BIOFILM")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Oral_Site",
fill = "Oral_Site",
shape = NULL,
filter_species = "Streptococcus_infantis",
filter_feature = diff_signif %>% filter(Species == "Streptococcus_infantis") %>% pull(Feature),
facet_formula = " . ~ Health_status ",
export_legend = TRUE) -> plot## Warning in if (filter_feature != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot
pwy %>%
dplyr::filter(Health_status == "Healthy control") %>%
dplyr::filter(Oral_Site %in% c("SALIVA", "TONGUE_BIOFILM")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Oral_Site",
fill = "Oral_Site",
shape = NULL,
filter_species = "Streptococcus_parasanguinis",
filter_feature = diff_signif %>% filter(Species == "Streptococcus_parasanguinis") %>% pull(Feature),
facet_formula = " . ~ Health_status ",
export_legend = TRUE) -> plot## Warning in if (filter_feature != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot
pwy %>%
dplyr::filter(Health_status == "Healthy control") %>%
dplyr::filter(Oral_Site %in% c("SALIVA", "TONGUE_BIOFILM")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Oral_Site",
fill = "Oral_Site",
shape = NULL,
filter_species = "Streptococcus_salivarius",
filter_feature = diff_signif %>% filter(Species == "Streptococcus_salivarius") %>% pull(Feature),
facet_formula = " . ~ Health_status ",
export_legend = TRUE) -> plot## Warning in if (filter_feature != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot
Fig3B: significant pathway expression by candidate species saliva versus plaque in health
redo main plot + stats
pwy %>%
dplyr::filter(Health_status == "Healthy control",
Oral_Site %in% c("SALIVA", "SUBGINGIVAL_PLAQUE")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Oral_Site",
fill = "Oral_Site",
shape = NULL,
filter_species = ma_saliva_plaque_strep_sel,
facet_formula = " . ~ Health_status + Species",
export_legend = TRUE) -> plot## Warning in if (filter_species != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot
plot$plot$data %>%
# mutate(log2RNA_DNA = log2(RNA_DNA)) %>%
ggpubr::compare_means(RNA_DNA ~ Oral_Site,
group.by = c("Species","Feature"),
data = .,
# method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) -> diff_signif
diff_signif %>%
DT::datatable()pwy %>%
dplyr::filter(Health_status == "Healthy control") %>%
dplyr::filter(Oral_Site %in% c("SALIVA", "SUBGINGIVAL_PLAQUE")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Oral_Site",
fill = "Oral_Site",
shape = NULL,
filter_species = "Streptococcus_oralis",
filter_feature = diff_signif %>% filter(Species == "Streptococcus_oralis") %>% pull(Feature),
facet_formula = " . ~ Health_status ",
export_legend = TRUE) -> plot## Warning in if (filter_feature != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot
pwy %>%
dplyr::filter(Health_status == "Healthy control") %>%
dplyr::filter(Oral_Site %in% c("SALIVA", "SUBGINGIVAL_PLAQUE")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Oral_Site",
fill = "Oral_Site",
shape = NULL,
filter_species = "Streptococcus_sanguinis",
filter_feature = diff_signif %>% filter(Species == "Streptococcus_sanguinis") %>% pull(Feature),
facet_formula = " . ~ Health_status ",
export_legend = TRUE) -> plot
plot$legend
plot$plot
# pwy %>%
# dplyr::filter(Health_status == "Healthy control") %>%
# dplyr::filter(Oral_Site %in% c("SALIVA", "SUBGINGIVAL_PLAQUE")) %>%
# # dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
# humann2_RNA_DNA_ratio_plot(x_plot = "name",
# y_plot = "log2(RNA_DNA)",
# color = "Oral_Site",
# fill = "Oral_Site",
# shape = NULL,
# filter_species = "Streptococcus_gordonii",
# filter_feature = diff_signif %>% filter(Species == "Streptococcus_gordonii") %>% pull(Feature),
# facet_formula = " . ~ Health_status ",
# export_legend = TRUE) -> plot
#
#
# plot$legend
# plot$plotFig 5. Overall bacterial activity of selected species in health versus diseases
Fig5A: box plot species in health and disease at each site
strep_sel <- c(ma_saliva_plaque_strep_sel, ma_saliva_tongue_strep_sel)pwy %>%
# dplyr::filter(Health_status == "Healthy control",
# Oral_Site %in% c("SALIVA", "TONGUE_BIOFILM")) %>%
# filter(RNA_DNA > mean(RNA_DNA, na.rm = TRUE)) %>%
# dplyr::filter(grepl("ose",name)) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "Species",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
filter_species = strep_sel,
facet_formula = ". ~ Oral_Site",
export_legend = TRUE) -> plot## Warning in if (filter_species != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot + ggpubr::rotate()
plot$plot$data %>%
ggpubr::compare_means(RNA_DNA ~ Health_status,
group.by = c("Oral_Site", "Species"),
data = .,
method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) %>%
DT::datatable()Fig5B: log DNA/Log RNA plots of species in health vs. disease at each site
# pwy %>%
# dplyr::filter(Health_status == "Healthy control",
# Oral_Site %in% c("SALIVA", "TONGUE_BIOFILM")) %>%
# humann2_RNA_DNA_plot(x_plot = "log10(DNA)",
# y_plot = "log10(RNA)",
# color = "Species",
# fill = "Species",
# shape = "Genus",
# group = "Species",
# filter_species = strep_sel,
# facet_formula = "Oral_Site ~ .") -> plot
pwy %>%
humann2_RNA_DNA_plot(x_plot = "log10(DNA)",
y_plot = "log10(RNA)",
color = "Species",
fill = "Species",
shape = "Genus",
group = "Species",
filter_species = strep_sel,
facet_formula = "Health_status ~ Oral_Site") -> plot## Warning in if (filter_species != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot
plot$plot$data %>%
select(-id, -sample_Sample, Health_status) %>%
group_by(Subject, Oral_Site) %>%
add_count(name = "count_per") %>%
slice_max(order_by = RNA, n = 3) %>%
DT::datatable()plot$plot$data %>%
select(-id, -sample_Sample, Health_status) %>%
group_by(Subject, Oral_Site) %>%
add_count(name = "count_per") %>%
slice_max(order_by = RNA_DNA, n = 3) %>%
DT::datatable()Fig 6 Pathway activity of selected species at each site in health versus disease
Fig6A-F: significant pathway expression by candidate species at each site in health and disease
pwy %>%
dplyr::filter(Species %in% strep_sel) %>%
# dplyr::filter(Oral_Site %in% c("SALIVA")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
# filter_species = "Streptococcus_infantis",
# filter_feature = diff_signif %>% filter(Species == "Streptococcus_infantis") %>% pull(Feature),
facet_formula = " . ~ Species + Oral_Site ",
export_legend = TRUE) -> plotplot$legend
plot$plot
A - SALIVA
strep_sel <- c(ma_saliva_plaque_strep_sel, ma_saliva_tongue_strep_sel)
strep_sel## [1] "Streptococcus_oralis" "Streptococcus_sanguinis"
## [3] "Streptococcus_gordonii" "Streptococcus_parasanguinis"
## [5] "Streptococcus_salivarius" "Streptococcus_infantis"Streptococcus_infantis
pwy %>%
dplyr::filter(Species %in% strep_sel) %>%
dplyr::filter(Oral_Site %in% c("SALIVA")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
filter_species = "Streptococcus_infantis",
# filter_feature = diff_signif %>% filter(Species == "Streptococcus_infantis") %>% pull(Feature),
facet_formula = " . ~ Species ",
export_legend = TRUE) -> plotplot$legend
plot$plot
plot$plot$data %>%
# mutate(log2RNA_DNA = log2(RNA_DNA)) %>%
ggpubr::compare_means(RNA_DNA ~ Health_status,
group.by = c("Feature"),
data = .,
# method = "wilcox.test",
p.adjust.method = "fdr") -> diff
diff %>%
filter(p.adj < 0.05) -> diff_signif
diff_signif %>%
DT::datatable()# pwy %>%
# dplyr::filter(Species %in% "Streptococcus_infantis") %>%
# dplyr::filter(Oral_Site %in% c("SALIVA")) %>%
# # dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
# humann2_RNA_DNA_ratio_plot(x_plot = "name",
# y_plot = "log2(RNA_DNA)",
# color = "Health_status",
# fill = "Health_status",
# shape = NULL,
# # filter_species = "Streptococcus_infantis",
# filter_feature = diff_signif %>% filter(Species == "Streptococcus_infantis") %>% pull(Feature),
# facet_formula = " . ~ Species ",
# export_legend = TRUE) -> plot
#
#
# plot$legend
# plot$plotStreptococcus_parasanguinis
pwy %>%
dplyr::filter(Species %in% strep_sel) %>%
dplyr::filter(Oral_Site %in% c("SALIVA")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
filter_species = "Streptococcus_parasanguinis",
# filter_feature = diff_signif %>% filter(Species == "Streptococcus_infantis") %>% pull(Feature),
facet_formula = " . ~ Species ",
export_legend = TRUE) -> plotplot$legend
plot$plot
plot$plot$data %>%
# mutate(log2RNA_DNA = log2(RNA_DNA)) %>%
ggpubr::compare_means(RNA_DNA ~ Health_status,
group.by = c("Feature"),
data = .,
# method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) -> diff_signif
diff_signif %>%
DT::datatable()pwy %>%
dplyr::filter(Species %in% "Streptococcus_parasanguinis") %>%
dplyr::filter(Oral_Site %in% c("SALIVA")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
# filter_species = "Streptococcus_infantis",
filter_feature = diff_signif %>% pull(Feature),
facet_formula = " . ~ Species ",
export_legend = TRUE) -> plot## Warning in if (filter_feature != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot
Streptococcus_salivarius
pwy %>%
dplyr::filter(Species %in% strep_sel) %>%
dplyr::filter(Oral_Site %in% c("SALIVA")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
filter_species = "Streptococcus_salivarius",
# filter_feature = diff_signif %>% filter(Species == "Streptococcus_infantis") %>% pull(Feature),
facet_formula = " . ~ Species ",
export_legend = TRUE) -> plotplot$legend
plot$plot
plot$plot$data %>%
# mutate(log2RNA_DNA = log2(RNA_DNA)) %>%
ggpubr::compare_means(RNA_DNA ~ Health_status,
group.by = c("Feature"),
data = .,
# method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) -> diff_signif
diff_signif %>%
DT::datatable()pwy %>%
dplyr::filter(Species %in% "Streptococcus_salivarius") %>%
dplyr::filter(Oral_Site %in% c("SALIVA")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
# filter_species = "Streptococcus_infantis",
filter_feature = diff_signif %>% pull(Feature),
facet_formula = " . ~ Species ",
export_legend = TRUE) -> plot## Warning in if (filter_feature != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot
Streptococcus_gordonii
pwy %>%
dplyr::filter(Species %in% strep_sel) %>%
dplyr::filter(Oral_Site %in% c("SALIVA")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
filter_species = "Streptococcus_gordonii",
# filter_feature = diff_signif %>% filter(Species == "Streptococcus_infantis") %>% pull(Feature),
facet_formula = " . ~ Species ",
export_legend = TRUE) -> plotplot$legend
plot$plot
plot$plot$data %>%
# mutate(log2RNA_DNA = log2(RNA_DNA)) %>%
ggpubr::compare_means(RNA_DNA ~ Health_status,
group.by = c("Feature"),
data = .,
# method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) -> diff_signif
diff_signif %>%
DT::datatable()# pwy %>%
# dplyr::filter(Species %in% "Streptococcus_gordonii") %>%
# dplyr::filter(Oral_Site %in% c("SALIVA")) %>%
# # dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
# humann2_RNA_DNA_ratio_plot(x_plot = "name",
# y_plot = "log2(RNA_DNA)",
# color = "Health_status",
# fill = "Health_status",
# shape = NULL,
# # filter_species = "Streptococcus_infantis",
# filter_feature = diff_signif %>% pull(Feature),
# facet_formula = " . ~ Species ",
# export_legend = TRUE) -> plot
#
#
# plot$legend
# plot$plotStreptococcus_sanguinis
pwy %>%
dplyr::filter(Species %in% strep_sel) %>%
dplyr::filter(Oral_Site %in% c("SALIVA")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
filter_species = "Streptococcus_sanguinis",
# filter_feature = diff_signif %>% filter(Species == "Streptococcus_infantis") %>% pull(Feature),
facet_formula = " . ~ Species ",
export_legend = TRUE) -> plotplot$legend
plot$plot
plot$plot$data %>%
# mutate(log2RNA_DNA = log2(RNA_DNA)) %>%
ggpubr::compare_means(RNA_DNA ~ Health_status,
group.by = c("Feature"),
data = .,
# method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) -> diff_signif
diff_signif %>%
DT::datatable()# pwy %>%
# dplyr::filter(Species %in% "Streptococcus_sanguinis") %>%
# dplyr::filter(Oral_Site %in% c("SALIVA")) %>%
# # dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
# humann2_RNA_DNA_ratio_plot(x_plot = "name",
# y_plot = "log2(RNA_DNA)",
# color = "Health_status",
# fill = "Health_status",
# shape = NULL,
# # filter_species = "Streptococcus_infantis",
# filter_feature = diff_signif %>% pull(Feature),
# facet_formula = " . ~ Species ",
# export_legend = TRUE) -> plot
#
#
# plot$legend
# plot$plotStreptococcus_oralis
pwy %>%
dplyr::filter(Species %in% strep_sel) %>%
dplyr::filter(Oral_Site %in% c("SALIVA")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
filter_species = "Streptococcus_oralis",
# filter_feature = diff_signif %>% filter(Species == "Streptococcus_infantis") %>% pull(Feature),
facet_formula = " . ~ Species ",
export_legend = TRUE) -> plotplot$legend
plot$plot
plot$plot$data %>%
# mutate(log2RNA_DNA = log2(RNA_DNA)) %>%
ggpubr::compare_means(RNA_DNA ~ Health_status,
group.by = c("Feature"),
data = .,
# method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) -> diff_signif
diff_signif %>%
DT::datatable()pwy %>%
dplyr::filter(Species %in% "Streptococcus_oralis") %>%
dplyr::filter(Oral_Site %in% c("SALIVA")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
# filter_species = "Streptococcus_infantis",
filter_feature = diff_signif %>% pull(Feature),
facet_formula = " . ~ Species ",
export_legend = TRUE) -> plot## Warning in if (filter_feature != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot
B - TONGUE_BIOFILM
strep_sel <- c(ma_saliva_tongue_strep_sel)
strep_sel## [1] "Streptococcus_parasanguinis" "Streptococcus_salivarius"
## [3] "Streptococcus_infantis"Streptococcus_infantis
pwy %>%
dplyr::filter(Species %in% strep_sel) %>%
dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
filter_species = "Streptococcus_infantis",
# filter_feature = diff_signif %>% filter(Species == "Streptococcus_infantis") %>% pull(Feature),
facet_formula = " . ~ Species ",
export_legend = TRUE) -> plotplot$legend
plot$plot
plot$plot$data %>%
# mutate(log2RNA_DNA = log2(RNA_DNA)) %>%
ggpubr::compare_means(RNA_DNA ~ Health_status,
group.by = c("Feature"),
data = .,
# method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) -> diff_signif
diff_signif %>%
DT::datatable()# pwy %>%
# dplyr::filter(Species %in% "Streptococcus_infantis") %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
# # dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
# humann2_RNA_DNA_ratio_plot(x_plot = "name",
# y_plot = "log2(RNA_DNA)",
# color = "Health_status",
# fill = "Health_status",
# shape = NULL,
# # filter_species = "Streptococcus_infantis",
# filter_feature = diff_signif %>% pull(Feature),
# facet_formula = " . ~ Species ",
# export_legend = TRUE) -> plot
#
#
# plot$legend
# plot$plotStreptococcus_parasanguinis
pwy %>%
dplyr::filter(Species %in% strep_sel) %>%
dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
filter_species = "Streptococcus_parasanguinis",
# filter_feature = diff_signif %>% filter(Species == "Streptococcus_infantis") %>% pull(Feature),
facet_formula = " . ~ Species ",
export_legend = TRUE) -> plotplot$legend
plot$plot
plot$plot$data %>%
# mutate(log2RNA_DNA = log2(RNA_DNA)) %>%
ggpubr::compare_means(RNA_DNA ~ Health_status,
group.by = c("Feature"),
data = .,
# method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) -> diff_signif
diff_signif %>%
DT::datatable()pwy %>%
dplyr::filter(Species %in% "Streptococcus_parasanguinis") %>%
dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
# filter_species = "Streptococcus_infantis",
filter_feature = diff_signif %>% pull(Feature),
facet_formula = " . ~ Species ",
export_legend = TRUE) -> plot## Warning in if (filter_feature != FALSE) {: the condition has length > 1 and only
## the first element will be usedplot$legend
plot$plot
Streptococcus_salivarius
pwy %>%
dplyr::filter(Species %in% "Streptococcus_salivarius") %>%
dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
filter_species = "Streptococcus_salivarius",
# filter_feature = diff_signif %>% filter(Species == "Streptococcus_infantis") %>% pull(Feature),
facet_formula = " . ~ Species ",
export_legend = TRUE) -> plotplot$legend
plot$plot
plot$plot$data %>%
# mutate(log2RNA_DNA = log2(RNA_DNA)) %>%
ggpubr::compare_means(RNA_DNA ~ Health_status,
group.by = c("Feature"),
data = .,
# method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) -> diff_signif
diff_signif %>%
DT::datatable()# pwy %>%
# dplyr::filter(Species %in% "Streptococcus_salivarius") %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
# # dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
# humann2_RNA_DNA_ratio_plot(x_plot = "name",
# y_plot = "log2(RNA_DNA)",
# color = "Health_status",
# fill = "Health_status",
# shape = NULL,
# # filter_species = "Streptococcus_infantis",
# filter_feature = diff_signif %>% pull(Feature),
# facet_formula = " . ~ Species ",
# export_legend = TRUE) -> plot
#
#
# plot$legend
# plot$plotC - SUBGINGIVAL_PLAQUE
strep_sel <- c(ma_saliva_plaque_strep_sel)
strep_sel## [1] "Streptococcus_oralis" "Streptococcus_sanguinis"
## [3] "Streptococcus_gordonii"Streptococcus_oralis
pwy %>%
dplyr::filter(Species %in% strep_sel) %>%
dplyr::filter(Oral_Site %in% c("SUBGINGIVAL_PLAQUE")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
filter_species = "Streptococcus_oralis",
# filter_feature = diff_signif %>% filter(Species == "Streptococcus_infantis") %>% pull(Feature),
facet_formula = " . ~ Species ",
export_legend = TRUE) -> plotplot$legend
plot$plot
plot$plot$data %>%
# mutate(log2RNA_DNA = log2(RNA_DNA)) %>%
ggpubr::compare_means(RNA_DNA ~ Health_status,
group.by = c("Feature"),
data = .,
# method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) -> diff_signif
diff_signif %>%
DT::datatable()# pwy %>%
# dplyr::filter(Species %in% "Streptococcus_infantis") %>%
# dplyr::filter(Oral_Site %in% c("SUBGINGIVAL_PLAQUE")) %>%
# # dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
# humann2_RNA_DNA_ratio_plot(x_plot = "name",
# y_plot = "log2(RNA_DNA)",
# color = "Health_status",
# fill = "Health_status",
# shape = NULL,
# # filter_species = "Streptococcus_infantis",
# filter_feature = diff_signif %>% pull(Feature),
# facet_formula = " . ~ Species ",
# export_legend = TRUE) -> plot
#
#
# plot$legend
# plot$plotStreptococcus_sanguinis
pwy %>%
dplyr::filter(Species %in% strep_sel) %>%
dplyr::filter(Oral_Site %in% c("SUBGINGIVAL_PLAQUE")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
filter_species = "Streptococcus_sanguinis",
# filter_feature = diff_signif %>% filter(Species == "Streptococcus_infantis") %>% pull(Feature),
facet_formula = " . ~ Species ",
export_legend = TRUE) -> plotplot$legend
plot$plot
plot$plot$data %>%
# mutate(log2RNA_DNA = log2(RNA_DNA)) %>%
ggpubr::compare_means(RNA_DNA ~ Health_status,
group.by = c("Feature"),
data = .,
# method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) -> diff_signif
diff_signif %>%
DT::datatable()# pwy %>%
# dplyr::filter(Species %in% "Streptococcus_sanguinis") %>%
# dplyr::filter(Oral_Site %in% c("SUBGINGIVAL_PLAQUE")) %>%
# # dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
# humann2_RNA_DNA_ratio_plot(x_plot = "name",
# y_plot = "log2(RNA_DNA)",
# color = "Health_status",
# fill = "Health_status",
# shape = NULL,
# # filter_species = "Streptococcus_infantis",
# filter_feature = diff_signif %>% pull(Feature),
# facet_formula = " . ~ Species ",
# export_legend = TRUE) -> plot
#
#
# plot$legend
# plot$plotStreptococcus_gordonii
pwy %>%
dplyr::filter(Species %in% strep_sel) %>%
dplyr::filter(Oral_Site %in% c("SUBGINGIVAL_PLAQUE")) %>%
# dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
humann2_RNA_DNA_ratio_plot(x_plot = "name",
y_plot = "log2(RNA_DNA)",
color = "Health_status",
fill = "Health_status",
shape = NULL,
filter_species = "Streptococcus_gordonii",
# filter_feature = diff_signif %>% filter(Species == "Streptococcus_infantis") %>% pull(Feature),
facet_formula = " . ~ Species ",
export_legend = TRUE) -> plotplot$legend
plot$plot
plot$plot$data %>%
# mutate(log2RNA_DNA = log2(RNA_DNA)) %>%
ggpubr::compare_means(RNA_DNA ~ Health_status,
group.by = c("Feature"),
data = .,
# method = "wilcox.test",
p.adjust.method = "fdr") %>%
filter(p.adj < 0.05) -> diff_signif
diff_signif %>%
DT::datatable()# pwy %>%
# dplyr::filter(Species %in% "Streptococcus_salivarius") %>%
# dplyr::filter(Oral_Site %in% c("SUBGINGIVAL_PLAQUE")) %>%
# # dplyr::filter(Oral_Site %in% c("TONGUE_BIOFILM")) %>%
# humann2_RNA_DNA_ratio_plot(x_plot = "name",
# y_plot = "log2(RNA_DNA)",
# color = "Health_status",
# fill = "Health_status",
# shape = NULL,
# # filter_species = "Streptococcus_infantis",
# filter_feature = diff_signif %>% pull(Feature),
# facet_formula = " . ~ Species ",
# export_legend = TRUE) -> plot
#
#
# plot$legend
# plot$plotsessionInfo()## R version 4.0.4 (2021-02-15)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Mojave 10.14.6
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] ggConvexHull_0.1.0 ampvis2_2.6.4 reshape2_1.4.4
## [4] scales_1.1.1 phyloseq_1.34.0 forcats_0.5.1
## [7] stringr_1.4.0 dplyr_1.0.4 purrr_0.3.4
## [10] readr_1.4.0 tidyr_1.1.2 tibble_3.1.0
## [13] ggplot2_3.3.3 tidyverse_1.3.0.9000
##
## loaded via a namespace (and not attached):
## [1] ggbeeswarm_0.6.0 Rtsne_0.15 colorspace_2.0-0
## [4] ggsignif_0.6.1 rio_0.5.26 ellipsis_0.3.1
## [7] XVector_0.30.0 fs_1.5.0 rstudioapi_0.13
## [10] ggpubr_0.4.0 farver_2.1.0 fantaxtic_0.1.0
## [13] ggrepel_0.9.1 ggnet_0.1.0 DT_0.17
## [16] fansi_0.4.2 lubridate_1.7.10 xml2_1.3.2
## [19] codetools_0.2-18 splines_4.0.4 doParallel_1.0.16
## [22] knitr_1.31 ade4_1.7-16 jsonlite_1.7.2
## [25] broom_0.7.5 cluster_2.1.1 dbplyr_2.1.0
## [28] compiler_4.0.4 httr_1.4.2 backports_1.2.1
## [31] assertthat_0.2.1 Matrix_1.3-2 lazyeval_0.2.2
## [34] cli_2.3.1 htmltools_0.5.1.1 prettyunits_1.1.1
## [37] tools_4.0.4 igraph_1.2.6 gtable_0.3.0
## [40] glue_1.4.2 Rcpp_1.0.6 carData_3.0-4
## [43] Biobase_2.50.0 cellranger_1.1.0 jquerylib_0.1.3
## [46] vctrs_0.3.6 Biostrings_2.58.0 rhdf5filters_1.2.0
## [49] multtest_2.46.0 ape_5.4-1 nlme_3.1-152
## [52] iterators_1.0.13 crosstalk_1.1.1 xfun_0.21
## [55] network_1.16.1 openxlsx_4.2.3 rvest_0.3.6
## [58] lifecycle_1.0.0 rstatix_0.7.0 zlibbioc_1.36.0
## [61] MASS_7.3-53.1 hms_1.0.0 parallel_4.0.4
## [64] biomformat_1.7.0 rhdf5_2.34.0 RColorBrewer_1.1-2
## [67] curl_4.3 yaml_2.2.1 speedyseq_0.5.3.9001
## [70] sass_0.3.1 stringi_1.5.3 highr_0.8
## [73] S4Vectors_0.28.1 foreach_1.5.1 permute_0.9-5
## [76] BiocGenerics_0.36.0 zip_2.1.1 rlang_0.4.10
## [79] pkgconfig_2.0.3 evaluate_0.14 lattice_0.20-41
## [82] Rhdf5lib_1.12.1 labeling_0.4.2 patchwork_1.1.1
## [85] htmlwidgets_1.5.3 cowplot_1.1.1 tidyselect_1.1.0
## [88] plyr_1.8.6 magrittr_2.0.1 R6_2.5.0
## [91] IRanges_2.24.1 generics_0.1.0 DBI_1.1.1
## [94] foreign_0.8-81 pillar_1.5.0 haven_2.3.1
## [97] withr_2.4.1 mgcv_1.8-34 abind_1.4-5
## [100] survival_3.2-7 car_3.0-10 modelr_0.1.8
## [103] crayon_1.4.1 utf8_1.1.4 microbiome_1.10.0
## [106] plotly_4.9.3 rmarkdown_2.7 progress_1.2.2
## [109] grid_4.0.4 readxl_1.3.1 data.table_1.14.0
## [112] vegan_2.5-7 reprex_1.0.0 digest_0.6.27
## [115] stats4_4.0.4 munsell_0.5.0 beeswarm_0.2.3
## [118] viridisLite_0.3.0 vipor_0.4.5 bslib_0.2.4